Karim R. Lakhani

Karim R. Lakhani is the Charles E. Wilson Professor of Business Administration and the Dorothy and Michael Hintze Fellow at the Harvard Business School. He is the founder and co-director of the Laboratory for Innovation Science at Harvard, the principal investigator of the NASA Tournament Laboratory at the Harvard Institute for Quantitative Social Science, and the faculty co-founder of the Harvard Business School Digital Initiative. He specializes in technology management and innovation. His research examines crowd-based innovation models and the digital transformation of companies and industries. Lakhani is known for his pioneering scholarship on how communities and contests can be designed and managed to achieve innovative outcomes. He has partnered with NASA, Topcoder, and the Harvard Medical School to conduct field experiments on the design of crowd innovation programs. His research on digital transformation has shown the importance of data and analytics as drivers of business and operating model transformation and source of competitive advantage. He serves on the Board of Directors of Mozilla Corporation and Local Motors.

Karim's research has been published in Harvard Business Review, Innovations, Journal of Organization Design, Management Science, Nature Biotechnology, Organization Science, RAND Journal of Economics, Research Policy and MIT Sloan Management Review. He is the co-editor of two books from MIT Press on distributed innovation models including Revolutionizing Innovation: Users, Communities and Open Innovation (2016) and Perspectives on Free and Open Source Software (2005). His research has been featured in BusinessWeek, The Boston Globe, The Economist, Fast Company, Inc., The New York Times, The New York Academy of Sciences Magazine, Science, The Wall Street Journal, The Washington Post, and Wired.

Karim has taught extensively in Harvard Business School’s MBA, executive and doctoral programs. He co-developed a new course on Digital Innovation and Transformation for the elective MBA curriculum and co-chairs the executive program on Competing with Big Data and Business Analytics. He is the co-chair of the Harvard Business Analytics Program, an online executive program training the next generation of data-savvy leaders.

Karim was awarded his Ph.D. in management from the Massachusetts Institute of Technology. He also holds an SM degree in Technology and Policy from MIT, and a Bachelor's degree in Electrical Engineering and Management from McMaster University in Canada. He was a recipient of the Aga Khan Foundation International Scholarship and a doctoral fellowship from Canada's Social Science and Humanities Research Council. Prior to coming to HBS he served as a Lecturer in the Technology, Innovation and Entrepreneurship group at MIT’s Sloan School of Management. Karim has also worked in sales, marketing and new product development roles at GE Healthcare and was a consultant with The Boston Consulting Group.

Featured Work

The last two decades have witnessed an extraordinary growth of new models of managing and organizing the innovation process that emphasizes users over producers. Large parts of the knowledge economy now routinely rely on users, communities, and open innovation approaches to solve important technological and organizational problems. This view of innovation, pioneered by the economist Eric von Hippel, counters the dominant paradigm, which cast the profit-seeking incentives of firms as the main driver of technical change. In a series of influential writings, von Hippel and colleagues found empirical evidence that flatly contradicted the producer-centered model of innovation. Since then, the study of user-driven innovation has continued and expanded, with further empirical exploration of a distributed model of innovation that includes communities and platforms in a variety of contexts and with the development of theory to explain the economic underpinnings of this still emerging paradigm. This volume provides a comprehensive and multidisciplinary view of the field of user and open innovation, reflecting advances in the field over the last several decades.

The contributors -- including many colleagues of Eric von Hippel -- offer both theoretical and empirical perspectives from such diverse fields as economics, the history of science and technology, law, management, and policy. The empirical contexts for their studies range from household goods to financial services. After discussing the fundamentals of user innovation, the contributors cover communities and innovation; legal aspects of user and community innovation; new roles for user innovators; user interactions with firms; and user innovation in practice, describing experiments, toolkits, and crowdsourcing, and crowdfunding.

We investigate the factors driving workers’ decisions to generate public goods inside an organization through a randomized solicitation of workplace improvement proposals in a medical center with 1200 employees. We find that pecuniary incentives, such as winning a prize, generate a threefold increase in participation compared to non-pecuniary incentives alone, such as prestige or recognition. Participation is also increased by a solicitation appealing to improving the workplace. However, emphasizing the patient mission of the organization led to countervailing effects on participation. Overall, these results are consistent with workers having multiple underlying motivations to contribute to public goods inside the organization consisting of a combination of pecuniary and altruistic incentives associated with the mission of the organization.

The ubiquity of digital technology and internet connectivity is driving both new and old players across all industries to invest in new capabilities, define new business models, and compete in new ways. From software to automobiles, from healthcare to financial services, models for value creation and value capture are evolving rapidly. In the Summit’s opening session, Prof. Karim R. Lakhani will give you insight into how organizations are transforming — to go far beyond simply remaining relevant, and to become innovative leaders in new and varied industries.

When Google bought Nest, a maker of digital thermostats, for $3.2 billion just a few months ago, it was a clear indication that digital transformation and connection are spreading across even the most traditional industrial segments and creating a staggering array of business opportunities and threats.

The digitization of tasks and processes has become essential to competition. General Electric, for example, was at risk of losing many of its top customers to nontraditional competitors—IBM and SAP on the one hand, big data start-ups on the other—offering data-intensive, analytics-based services that could connect to any industrial device. So GE launched a multibillion-dollar initiative focused on what it calls the industrial internet: adding digital sensors to its machines; connecting them to a common, cloud-based software platform; investing in software development capabilities; building advanced analytics capabilities; and embracing crowd-based product development. With all this, GE is evolving its business model. Now, for example, revenue from its jet engines is tied to reduced downtime and miles flown over the course of a year. After just three years, GE is generating more than $1.5 billion in incremental income with digitally enabled, outcomes-based business models. The company expects that number to double in 2014 and again in 2015.

From Apple to Merck to Wikipedia, more and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious. It seems risky and even unnatural to push problems out to vast groups of strangers distributed around the world, particularly for companies built on a history of internal innovation. How can intellectual property be protected? How can a crowdsourced solution be integrated into corporate operations? What about the costs?

These concerns are all reasonable, the authors write, but excluding crowdsourcing from the corporate innovation tool kit means losing an opportunity. After a decade of study, they have identified when crowds tend to outperform internal organizations (or not). They outline four ways to tap into crowd-powered problem solving—contests, collaborative communities, complementors, and labor markets—and offer a system for picking the best one in a given situation. Contests, for example, are suited to highly challenging technical, analytical, and scientific problems; design problems; and creative or aesthetic projects. They are akin to running a series of independent experiments that generate multiple solutions—and if those solutions cluster at some extreme, a company can gain insight into where a problem’s “technical frontier” lies. (Internal R&D may generate far less information.)

February 26, 2016, Entrepreneurship and Small Business Research Institute

Innovation has become an urgent imperative for entrepreneurial and established organizations. Over the last decade, in industries as diverse as fashion design, media software, life sciences, pharmaceuticals and automotive, the most cutting edge organizations have started to externalize their innovation process by working actively with communities and sponsoring contests – so called open innovation. At this lecture, Karim Lakhani from Harvard Business School will provide best practice examples and a framework for using communities and contests to solve the most pressing innovation problems.

He is the Principal Investigator of The Crowd Innovation Lab at Harvard's Institute for Quantitative Social Science, which has worked closely with strategic partners at NASA, Harvard Medical School, Scripps Research Institute, various US government agencies and private sector partners. The idea is to solve innovation problems while simultaneously driving social science insights on the optimal organization of crowd-based innovation. Professor Lakhani will also discuss the Lab's experience in working with its strategic partners to drive change in the organization of innovation.

Legislation in Congress could make it easier for everyday people to become investors in small companies. Harvard Business School’s Karim Lakhani and entrepreneur Slava Menn tell Kara why “crowdfunding” is all the rage.

Through a renewed focus on innovation and technology, NASA seeks to be an important catalyst for intellectual and economic expansion for the nation. Our inaugural TechNovation Speaker Forum gathered NASA employees from across the agency to listen to our special presenter Karim R. Lakhani, an assistant professor at Harvard Business School who specializes in management of technological innovation and product development in firms and communities. Lakhani discussed innovative approaches to solving problems by leveraging the knowledge of virtual communities, known as "the cloud" and by using distributed or open innovations. The program was carried live on NASA Television with Q&A from participating NASA centers.

For the forum's topic of collective intelligence, Karim Lakhani participated as a speaker in "a conversation about the theory and practice of collective intelligence, with emphasis on Wikipedia, other instances of aggregated intellectual work and on recent innovative applications in business." A podcast and a webcast are available through the forum's website.

by Karim R. Lakhani and Andrew P. McAfee, Harvard Business School Case, January 30, 2007

On August 24, 2006, the "Enterprise 2.0" entry in the Web-based encyclopedia Wikipedia was made a candidate for deletion. Wikipedia was an unusual encyclopedia because virtually anybody could start a new article or edit an existing one. This egalitarian philosophy had enabled very rapid growth but also led to the creation of some articles that did not meet established standards. Wikipedia's "articles-for-deletion" (AfD) process was an attempt to deal with this problem. Anyone could nominate an article for deletion; nomination caused a notice to be placed on the article's page alerting readers to the deletion request and pointing them to a special page where they could debate it. An AfD process lasted five days, after which a Wikipedia administrator reviewed the arguments and made a decision on the fate of the article.

In the spirit of Wikipedia we have released this under a GFDL license, and we will teach it in Andrew McAfee's second year MBA course on Managing in the Information Age this Spring to get students familiar with the inner workings of a distributed community and to grapple with issues related to authority, decision making, expertise and norms of behavior in a community setting.

What is the status of the Free and Open Source Software (F/OSS) revolution? Has the creation of software that can be freely used, modified, and redistributed transformed industry and society, as some predicted, or is this transformation still a work in progress? Perspectives on Free and Open Source Software brings together leading analysts and researchers to address this question, examining specific aspects of F/OSS in a way that is both scientifically rigorous and highly relevant to real-life managerial and technical concerns.

Publications

The last two decades have witnessed an extraordinary growth of new models of managing and organizing the innovation process, which emphasize users over producers. Large parts of the knowledge economy now routinely rely on users, communities, and open innovation approaches to solve important technological and organizational problems. This view of innovation, pioneered by the economist Eric von Hippel, counters the dominant paradigm, which casts the profit-seeking incentives of firms as the main driver of technical change. In a series of influential writings, von Hippel and colleagues found empirical evidence that flatly contradicted the producer-centered model of innovation. Since then, the study of user-driven innovation has continued and expanded, with further empirical exploration of a distributed model of innovation that includes communities and platforms in a variety of contexts and with the development of theory to explain the economic underpinnings of this still emerging paradigm. This volume provides a comprehensive and multidisciplinary view of the field of user and open innovation, reflecting advances in the field over the last several decades. The contributors—including many colleagues of Eric von Hippel—offer both theoretical and empirical perspectives from such diverse fields as economics, the history of science and technology, law, management, and policy. The empirical contexts for their studies range from household goods to financial services. After discussing the fundamentals of user innovation, the contributors cover communities and innovation; legal aspects of user and community innovation; new roles for user innovators; user interactions with firms; and user innovation in practice, describing experiments, toolkits, and crowdsourcing and crowdfunding.

Background: Frontline staff are well positioned to conceive improvement opportunities based on first-hand knowledge of what works and does not work. The innovation contest may be a relevant and useful vehicle to elicit staff ideas. However, the success of the contest likely depends on perceived organizational support for learning; when staff believe that support for learning-oriented culture, practices, and leadership is low, they may be less willing or able to share ideas. Purpose: We examined how staff perception of organizational support for learning affected contest participation, which comprised ideation and evaluation of submitted ideas. Methodology/Approach: The contest held in a hospital cardiac center invited all clinicians and support staff (n = 1,400) to participate. We used the 27-item Learning Organization Survey to measure staff perception of learning-oriented environment, practices and processes, and leadership. Results: Seventy-two frontline staff submitted 138 ideas addressing wide-ranging issues including patient experience, cost of care, workflow, utilization, and access. Two hundred forty-five participated in evaluation. Supportive learning environment predicted participation in ideation and idea evaluation. Perceptions of insufficient experimentation with new ways of working also predicted participation. Conclusion: The contest enabled frontline staff to share input and assess input shared by other staff. Our findings indicate that the contest may serve as a fruitful outlet through which frontline staff can share and learn new ideas, especially for those who feel safe to speak up and believe that new ideas are not tested frequently enough. Practice Implications: The contest’s potential to decentralize innovation may be greater under stronger learning orientation. A highly visible intervention, like the innovation contest, has both benefits and risks. Our findings suggest benefits such as increased engagement with work and community as well as risks such as discontent that could arise if staff suggestions are not acted upon or if there is no desired change after the contest.

We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators. We generated exogenous variation in search costs for pairs of potential collaborators by randomly assigning individuals to 90-minute structured information-sharing sessions as part of a grant funding opportunity. We estimate that the treatment increases the probability of grant co-application of a given pair of researchers by 75%. The findings suggest that matching between scientists is subject to considerable friction, even in the case of geographically proximate scientists working in the same institutional context.

BACKGROUND:
The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets.
RESULTS:
Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project.
CONCLUSIONS:
Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics.

A small number of digital superpowers—Alibaba, Amazon, Microsoft, and others—have become “hub firms” because they control access to billions of mobile customers coveted by all kinds of product and service providers. These hubs drive increasing returns to scale and claim a disproportionate share of the value being created in the global economy. The authors argue that the hub economy will continue to spread across more industries, concentrating more power in the hands of a few. As an example, they take an in-depth look at the auto industry and how Apple and Alphabet/Google are poised to become the main beneficiaries as cars turn into digitally connected spaces for work, entertainment, and shopping. As hubs proliferate and expand their reach, the danger is that they will exacerbate economic inequality and threaten social stability. It is thus incumbent on all stakeholders—traditional companies, start-ups, institutions, and communities—to make certain changes in the ways they do business. Moreover, hub firms themselves must do a better job leading responsibly for the good of all, not just creating and capturing value but doing more to sustain other players in the ecosystem.

The purpose of this article is to suggest a (preliminary) taxonomy and research agenda for the topic of “firms, crowds, and innovation” and to provide an introduction to the associated special issue. We specifically discuss how various crowd-related phenomena and practices—for example, crowdsourcing, crowdfunding, user innovation, and peer production—relate to theories of the firm, with particular attention on “sociality” in firms and markets. We first briefly review extant theories of the firm and then discuss three theoretical aspects of sociality related to crowds in the context of strategy, organizations, and innovation: (1) the functions of sociality (sociality as extension of rationality, sociality as sensing and signaling, sociality as matching and identity); (2) the forms of sociality (independent/aggregate and interacting/emergent forms of sociality); and (3) the failures of sociality (misattribution and misapplication). We conclude with an outline of future research directions and introduce the special issue papers and essays.

Contracts, transactions, and records of them provide critical structure in our economic system, but they haven’t kept up with the world’s digital transformation. They’re like rush-hour gridlock trapping a Formula 1 race car. Blockchain promises to solve this problem. The technology behind bitcoin, blockchain is an open, distributed ledger that records transactions safely, permanently and very efficiently. For instance, while the transfer of a share of stock can now take up to a week, with blockchain it could happen in seconds. Blockchain could slash the cost of transactions and eliminate intermediaries like lawyers and bankers, and that could transform the economy. But, like the adoption of more Internet technologies, blockchain’s adoption will require broad coordination and will take years. The authors describe the path that blockchain is likely to follow and explain how firms should think about investments in it.

Tournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data from 2,796 contestants in 774 software algorithm design contests with random assignment. Precisely conforming to theory predictions, the performance response to added contestants varies non-monotonically across contestants of different abilities, most respond negatively to competition, and highest-skilled contestants respond positively. In counterfactual simulations, we interpret a number of tournament design policies (number of competitors, prize allocation and structure, divisionalization, open entry) as a means of reconciling non-monotonic incentive responses to competition, effectively manipulating the number and skills distribution of contestants facing one another.

Selecting among alternative innovative projects is a core management task in all innovating organizations. In this paper, we focus on the evaluation of frontier scientific research projects. We argue that the "intellectual distance" between the knowledge embodied in research proposals and an evaluator's own expertise systematically relates to the evaluations given (and consequent resource allocation). We empirically evaluate effects in data collected from a grant proposal process at a leading research university in which we randomized the assignment of evaluators and proposals to generate 2,130 evaluator-proposal pairs. We find evaluators systematically give lower scores to research proposals closer to their own areas of expertise and to highly novel research proposals. We interpret the empirical patterns in relation to a range of theoretical mechanisms and discuss implications for policy, managerial intervention, and allocation of resources in the ongoing accumulation of scientific knowledge.

Most of society's innovation systems―academic science, the patent system, open source, etc.―are "open" in the sense that they are designed to facilitate knowledge disclosure among innovators. An essential difference across innovation systems is whether disclosure is of intermediate progress and solutions or of completed innovations. We present experimental evidence that links intermediate versus final disclosure not just with quantitative tradeoffs that shape the rate of innovation, but also with transformation of the very nature of the innovation search process. We find intermediate disclosure has the advantage of efficiently steering development towards improving existing solution approaches, but also the effect of limiting experimentation and narrowing technological search. We discuss the comparative advantages of intermediate versus final disclosure policies in fostering innovation.

When Google bought Nest, a maker of digital thermostats, for $3.2 billion just a few months ago, it was a clear indication that digital transformation and connection are spreading across even the most traditional industrial segments and creating a staggering array of business opportunities and threats.
The digitization of tasks and processes has become essential to competition. General Electric, for example, was at risk of losing many of its top customers to nontraditional competitors—IBM and SAP on the one hand, big data start-ups on the other—offering data-intensive, analytics-based services that could connect to any industrial device. So GE launched a multibillion-dollar initiative focused on what it calls the industrial internet: adding digital sensors to its machines; connecting them to a common, cloud-based software platform; investing in software development capabilities; building advanced analytics capabilities; and embracing crowd-based product development. With all this, GE is evolving its business model. Now, for example, revenue from its jet engines is tied to reduced downtime and miles flown over the course of a year. After just three years, GE is generating more than $1.5 billion in incremental income with digitally enabled, outcomes-based business models. The company expects that number to double in 2014 and again in 2015.

More and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious. It seems risky and even unnatural to push problems out to vast groups of strangers distributed around the world, particularly for companies built on a history of internal innovation. How can intellectual property be protected? How can a crowdsourced solution be integrated into corporate operations? What about the costs? These concerns are all reasonable, but excluding crowdsourcing from the corporate innovation tool kit means losing an opportunity. After a decade of study, we have identified when crowds tend to outperform internal organizations (or not). We outline four ways to tap into crowd-powered problem solving—contests, collaborative communities, complementors, and labor markets—and offer a system for picking the best one in a given situation. We emphasize that crowds are complementary to internal innovation efforts and present a new capability for firms that want to accelerate their innovation outcomes.

Harvard Medical School seems an unlikely organization to open up its innovation process. By most measures, the more than 20,000 faculty, research staff and graduate students affiliated with Harvard Medical School are already world class and at the top of the medical research game, with approximately $1.4 billion in annual funding from the U.S. National Institutes of Health (NIH). But in February 2010, Drew Faust, president of Harvard University, sent an email invitation to all faculty, staff and students at the university (more than 40,000 individuals) encouraging them to participate in an ideas challenge that Harvard Medical School had launched to generate research topics in Type 1 diabetes. Eventually, the challenge was shared with more than 250,000 invitees, resulting in 150 research ideas and hypotheses. The goal of opening up idea generation and disaggregating the different stages of the research process was to expand the number and range of people who might participate. Today, seven teams of multi-disciplinary researchers are working on the resulting potential breakthrough ideas. In this article, we describe how leaders of Harvard Catalyst, an organization whose mission is to drive therapies from the lab to patients' bedsides faster and to do so by working across the many silos of Harvard Medical School, chose to implement principles of open and distributed innovation.

Which parts of your innovation processes should you open up to the wider world? To reap the benefits of open innovation, executives must understand what to open, how to open it, and how to manage the resulting problems. According to authors Andrew King of Dartmouth College's Tuck School of Business and Karim R. Lakhani of the Harvard Business School and the NASA Tournament Lab, many organizations "are finding that making open innovation work can be more complicated than it looks."

Contests are a historically important and increasingly popular mechanism for encouraging innovation. A central concern in designing innovation contests is how many competitors to admit. Using a unique data set of 9,661 software contests, we provide evidence of two coexisting and opposing forces that operate when the number of competitors increases. Greater rivalry reduces the incentives of all competitors in a contest to exert effort and make investments. At the same time, adding competitors increases the likelihood that at least one competitor will find an extreme-value solution. We show that the effort-reducing effect of greater rivalry dominates for less uncertain problems whereas the effect on the extreme value prevails for more uncertain problems. Adding competitors thus systematically increases overall contest performance for high-uncertainty problems. We also find that higher uncertainty reduces the negative effect of added competitors on incentives. Thus uncertainty and the nature of the problem should be explicitly considered in the design of innovation tournaments. We explore the implications of our findings for the theory and practice of innovation contests.

We examine who the winners are in science problem-solving contests characterized by open broadcast of problem information, self-selection of external solvers to discrete problems from the laboratories of large R&D intensive companies, and blind review of solution submissions. We find that technical and social marginality, being a source of different perspectives and heuristics, plays an important role in explaining individual success in problem solving. The provision of a winning solution was positively related to increasing distance between the solver's field of technical expertise and the focal field of the problem. Female solvers—known to be in the "outer circle" of the scientific establishment—performed significantly better than men in developing successful solutions. Our findings contribute to the emerging literature on open and distributed innovation by demonstrating the value of openness, at least narrowly defined by disclosing problems, in removing barriers to entry to non-obvious individuals. We also contribute to the knowledge-based theory of the firm by showing the effectiveness of a market mechanism to draw out knowledge from diverse external sources to solve internal problems.

This paper discusses several challenges in designing field experiments to better understand how organizational and institutional design shapes innovation outcomes and the production of knowledge. We proceed to describe the field experimental research program carried out by our Crowd Innovation Laboratory at Harvard University to clarify how we have attempted to address these research design challenges. This program has simultaneously solved important practical innovation problems for partner organizations, like NASA and Harvard Medical School, while contributing research advances, particularly in relation to innovation contests and tournaments.

This chapter contrasts traditional, organization-centered models of innovation with more recent work on open innovation. These fundamentally different and inconsistent innovation logics are associated with contrasting organizational boundaries and organizational designs. We suggest that when critical tasks can be modularized and when problem-solving knowledge is widely distributed and available, open innovation complements traditional innovation logics. We induce these ideas from the literature and with extended examples from Apple, NASA, and LEGO. We suggest that task decomposition and problem-solving knowledge distribution are not deterministic but are strategic choices. If dynamic capabilities are associated with innovation streams, and if different innovation types are rooted in contrasting innovation logics, there are important implications for firm boundaries, design, and identity.

Software development occurs in a patchwork or "confederacy" of different types of institutions (universities, small start-ups, multinational enterprises, government agencies, etc.) utilizing varied work approaches. Here we speculate on one possible explanation for this organizational heterogeneity: it may reflect inherent heterogeneity of the software workforce, in terms of which kinds of organizations individual workers prefer to work within ("institutional preference"). We take very preliminary steps towards investigating this possibility by devising a novel 10-day field experiment to estimate the differences in behavior that are created by sorting workers into their preferred institutional regimes versus having them unsorted. The experiment involved assigning 1,040 elite software developers to either a competitive or a cooperative work regime to create software for NASA's Space Life Sciences Directorate. Half of the subjects-the "sorted" group-were assigned according to their institutional preferences; the other half-the "unsorted" group-were assigned without regard to their preferences. Assignment was done in a manner where sorted and unsorted groups had identical distributions of raw problem-solving ability. We find a remarkably large effect of institutional preference-based sorting on the effort exerted. Sorting on institutional preferences roughly doubled effort within the competitive regime and increased effort by roughly half in the cooperative regime, while accounting for incentives. Our experimental approach and results indicate the importance of accounting for worker preferences in creative activities that drive the rate and direction of inventive activity in the economy.

O'Mahony, Siobhan, and Karim R. Lakhani. "Organizations in the Shadow of Communities." In Communities and Organizations. Vol. 33, edited by Christopher Marquis, Michael Lounsbury, and Royston Greenwood, 336. Research in the Sociology of Organizations. Emerald Group Publishing, 2011.
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We investigate the factors driving workers’ decisions to generate public goods inside an organization through a randomized solicitation of workplace improvement proposals in a medical center with 1,200 employees. We find that pecuniary incentives, such as winning a prize, generate a threefold increase in participation compared to non-pecuniary incentives alone, such as prestige or recognition. Participation is also increased by a solicitation appealing to improving the workplace. However, emphasizing the patient mission of the organization led to countervailing effects on participation. Overall, these results are consistent with workers having multiple underlying motivations to contribute to public goods inside the organization consisting of a combination of pecuniary and altruistic incentives associated with the mission of the organization.

Innovation requires sources of novelty, but the challenge is that not all sources lead to innovation, so its value needs to be determined. However, since ways of determining value stem from existing knowledge, this often creates barriers to innovation. To understand how people address the challenge of novelty, we develop a conceptual and an empirical framework to explain how this challenge is addressed in a software and scientific context. What is shown is that the process of innovation is a cycle where actors develop a novel course of action and, based on the consequences identified, confirm what knowledge is necessary to transform and develop the next course of action. The performance of the process of innovation is constrained by the capacities of the artifacts and the ability of the actors to create and use artifacts to drive this cycle. By focusing on the challenge of novelty, a problem that cuts across all contexts of innovation, our goal is to develop a more generalized account of what drives the process of innovation.

EmQuest, Emirates Group’s travel distribution company, must decide what to do with its contract with the global distribution system it uses, Sabre. Since its founding in 1988, EmQuest was servicing travel agents in the MENA region by providing a connection to over 400 airlines as well as numerous other travel suppliers. EmQuest mainly relied on Sabre to provide this service to the agents, and its contract was coming to an end.
In the last decade years, since the beginning of EmQuest’s Sabre contract, while EmQuest grew, a lot happened in the travel industry: the Internet transformed customer habits, low-cost carriers emerged, and the Middle East experienced a boom in tourism. The conditions under which EmQuest had first signed its contract with Sabre a decade before were much different in 2017.
With change happening so rapidly and impacting the fundamentals of the travel business model so dramatically, it was a real challenge to predict where the industry would be in the next decade. Yet the management needed to make a decision regarding the Sabre contract in 2017, amidst such a whirlwind in the market.

BACKGROUND:
The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets.
RESULTS:
Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project.
CONCLUSIONS:
Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics.

In 2017, the co-founders of BlaBlaCar—the world’s largest long-distance carpooling company—reflected on the evolution of their venture and the way forward. BlaBlaCar had reached critical mass and size; yet staying still was not going to be enough to be relevant and competitive in the hyper competitive sharing economy sector. The co-founders felt that the time was now to capitalize on the trust that the platform had built with its members and explore adjacent opportunities. The options in front of them represented a wide variety of ways to grow, but how should the team prioritize and figure out which opportunities represented a viable business strategy for their company?

Tomohiro Ishibashi (Bashi), chief executive officer for B to S, and Julia Foote LeStage, chief innovation officer of Weathernews Inc., were addressing a panel at the HBS Digital Summit on creative uses of big data. They told the summit attendees about how the Sakura (cherry blossoms) Project, where the company asked users in Japan to report about how cherry blossoms were blooming near them day by day, had opened up opportunities for the company's consumer business in Japan. The project ultimately garnered positive publicity and became a foothold to building the company's crowdsourcing weather-forecasting service in Japan. It changed the face of weather forecasting in Japan. Bashi and LeStage wondered whether the experience could be applied to the U.S. market.

Following the March 2016 launch of DB11, Aston Martin Lagonda Ltd.’s first new sports car platform in over a decade, this case discusses the future strategy of the famed British luxury auto manufacturer. Since its founding in 1902, Aston Martin has been characterized by leading automotive design of bespoke luxury vehicles. In 2016, CEO Andy Palmer faced decisions about the company’s future direction in an automotive industry in the midst of a digital tornado with the arrival of autonomous, internetworked, clean-energy-propelled vehicles. Palmer’s Second Century Plan called for Aston Martin to diversify into new vehicle categories and increase overall production volume in an effort to boost earnings without compromising Aston Martin’s reputation for exclusivity, style, and engineering. As one of the few luxury car companies not backed by a larger automaker, Palmer and Aston Martin faced the challenge of funding the development of new vehicles and maintaining a position of leadership in automotive design. “The big question is whether the Second Century Plan has us departing from our traditional role as a sports car and luxury manufacturer and moving into new segments, new businesses,” said Palmer in late 2016. “Is that a wise choice? How does a high-end premium provider in any business grow without losing its exclusive reputation? That is the eternal business question.”

In 2015, German football club Bayern Munich is considering how to enter the Chinese market. Should it build its own infrastructure or rely on third-party partnerships to reach this massive football fan base?

In 2015, Dietmar Hopp, owner of Germany's Bundesliga football team TSG Hoffenheim and co-founder of the global enterprise software company SAP, was considering how to ensure long-term sustainability and competitiveness for TSG Hoffenheim. While historically a small team from bottom rungs of the league, TSG Hoffenheim, with revenues of €60 million to €70 million, reached the top division of the Bundesliga in the 2008–2009 season thanks to a deliberate strategy focused on enhanced scouting, strong youth programs, and innovative technology and analytics that improved player development. In 2014 Hopp, who had personally invested €300 million in the club, built a "footbonaut," an automated training environment that collected data on players' skills and strengths. The tool, one of three in the world, helped scouts and coaches better assess and develop each player. Yet some managers felt the technology was a distraction, an investment too expensive for a team that was not yet cash-flow positive. The team finished the 2014–2015 season in eighth place, below the top division, and Hopp wondered whether the focus on technology and analytics was the right strategy to grow the club. He wondered if the "moneyball" approach—when a smaller team competed with wealthier teams by using statistical analysis to buy undervalued assets and sell overvalued assets—could work in football and if investments in technology could lead the team to financial independence.

To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes several methods for gaining insights into causal relations, including randomized experiments, panel data, matching, and regression discontinuity. The note is intended for a general audience and does not require advanced statistics knowledge.

By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning algorithms to evaluate the abilities of job seekers and provide feedback by measuring not only skills and knowledge, but also personality and behavior traits. Since its founding in 2007, the company developed several new assessment products, including SVAR, a spoken-English evaluation, Automata, a programming skills evaluator, a customer service test, and TESLA, a suite of products that assessed and provided certification for vocational skills. The company had recently expanded into parts of Africa, the Middle East, the Philippines, the U.S., and most recently, China. Aspiring Minds had seen success as a business-to-business (B2B) entity, creating and selling technology products geared towards industry verticals. By 2015 the business-to-consumer (B2C) side of the business in India had been quite successful as well, generating revenues equal to that of the B2B side. As Aspiring Minds worked to establish a presence in China, co-founders Himanshu and Varun Aggarwal considered whether a B2B or B2C approach would best help the company achieve scale.

BandPage CEO James "J" Sider is about to receive results from BandPage's targeted advertising campaign on music streaming service Rhapsody and learn whether BandPage's strategy to improve ad click through rates and generate revenue has succeeded. BandPage, which began as a Facebook app to help musicians build professional-looking pages and convert fan "likes" into revenue, has become a major hub in the online music network. BandPage has deals with upstream and downstream music partners, from streaming services to ticket sellers to merchandise companies, and has built relationships with artists by providing a one stop shop to update current band information across most major music sites simultaneously. BandPage's most recent project has been to differentiate fans by their behavior on streaming sites in order to target super fans with high priced, exclusive and/or personalized offers from artists. At a time when tensions are high between streaming services and artists who believe that they are not being fairly compensated for the use of their music, Sider is convinced that BandPage can help streaming services drive revenue growth for artists through ticket, merchandise and exclusive offer sales. If the Rhapsody data proves that BandPage's strategy is working, the potential revenue growth for BandPage and all of its partners is massive.

This note examines the evolution of the thermostat industry as it transitioned from analog to digital technologies. It presents an overview of key industry participants and the shift in value creation and value capture models for firms.

Victors & Spoils (V&S), located in Boulder, Colorado, was the first advertising agency built on open innovation and crowdsourcing principles from the ground-up. V&S was co-founded in 2009 by John Winsor, Claudia Batten and Evan Fry, all former members of the advertising agency Crispin Porter + Bogusky (CP+B). V&S crowdsourced creative ideas for its ad campaigns through Agency Machine, its proprietary online platform. CEO John Winsor wanted to change the way that advertising was done, a difficult task in an industry entrenched in traditional models. The case follows Winsor as he prepares to scale his business and must determine the best way to do so. He has an offer from Havas, a leading global advertising company interested in acquiring V&S, which would give V&S access to unprecedented resources. However, Winsor and the V&S team have concerns about how their innovative processes may be affected by partnering with a large, traditional company.

As of 2013, Havas was the 6th largest global advertising, digital, and communications group in the world. Headquartered in Paris, France, the group was highly decentralized, with semi-independent agencies in more than 100 countries offering a variety of services. The largest unit of Havas was Havas Worldwide, an integrated marketing communications agency headquartered in New York, NY. CEO David Jones was determined to make Havas Worldwide the most future-focused agency in the industry by becoming a leader in digital innovation. The case explores the tensions within the company as David Jones attempts to change the company to compete in an industry undergoing digital transformation. The case uses the example of the acquisition of Victors & Spoils, a crowdsourcing advertising agency, to examine internal reactions.

This supplemental case follows up on the Netflix Prize Contest described in Netflix: Designing the Netflix Prize (A). In the A case, Netflix CEO Reed Hastings must decide how to organize a crowdsourcing contest to improve the algorithms for Netflix's movie recommendation software. The B case follows the contest from the building of the platform in 2006 to the awarding of the highest prize in 2009. The B case also considers the aftermath of the contest, and the issues of successfully implementing a winning idea from a contest.

In 2006, Reed Hastings, CEO of Netflix, was looking for a way to solve Netflix's customer churn problem. Netflix used Cinematch, its proprietary movie recommendation software, to promote individually determined best-fit movies to customers. Hastings determined that a 10% improvement to the Cinematch algorithm would decrease customer churn and increase annual revenue by up to $89 million. However, traditional options for improving the algorithm, such as hiring and training new employees, were time intensive and costly. Hastings decided to improve Netflix's software by crowdsourcing, and began planning the Netflix Prize, an open contest searching for a 10% improvement on Cinematch. The case examines the dilemmas Hastings faced as he planned the contest, such as whether to use an existing crowdsourcing platform or create his own, what company information to expose, how to protect customer privacy while making internal datasets public, how to allocate IP, and how to manage the crowd.

CEO Jeff Immelt considers whether GE is moving fast enough on its new Industrial Internet initiative. The undertaking includes building out an Industrial Internet, connecting machines and devices, collecting their data and operations, and providing services to clients based on analytics of this data and information. The case considers the implications of such an initiative across all 6 of GE's business units, and how best and how quickly to execute the strategy. The firm has committed $1b in investment, building out a new software center in California, and a commercial sales function at headquarters to deploy the new products and services.

Mark Fields, Ford Motor Company's COO, had to ensure the company's current business model of building cars and trucks remained strong, while concurrently navigating the company into the rapidly expanding industry of personal mobility. Personal mobility required new technologies and business models that were untraditional at Ford, and Fields had to evaluate the traditional business model colliding with the new business model.
To direct these new technologies and business models, Ford released its "Blueprint for Mobility," which established near-, mid- and long-term goals to make mobility accessible and affordable to all.
The case focuses on the launch of three mobility experiments (car sharing, parking, and on-demand ride sharing), and asks students to determine how Fields should balance these types of experiments with the company's traditional operations. Further, was Ford doing enough in the mobility space, and if so, was it moving fast enough? What new sources of revenue could Ford derive from mobility solutions?

This case follows Rodrigo Nino, founder and CEO of commercial real estate development company Prodigy Network, as he develops an equity-based crowdfunding model for small investors to access commercial real estate in Colombia, then tries out the model in the U.S. U.S. regulations, starting with the Securities Act of 1933, effectively barred sponsors from soliciting small investors for large commercial real estate. However, the JOBS Act of 2013 loosened U.S. restrictions on equity crowdfunding. Nino believes that crowdfunding will democratize real estate development by providing a new asset class for small investors, revolutionizing the industry. The case also follows Nino's development of an online platform to crowdsource design for his crowdfunded buildings, maximizing shared value throughout the development process. Nino faces many challenges as he attempts to crowdfund an extended stay hotel in Manhattan, New York. For example, crowdfunded real estate faces resistance from industry leaders, especially in regards to the concern of fraud, and SEC regulations on crowdfunding remain undetermined at the time of the case.

From the late 1990s to 2006/2007, Samsung Electronics moved from one of 170 TV manufacturers to gain dominant TV market share year over year from 2007-2013. As digital technologies increasingly converged in 2013-2014, the industry faced new questions: What was the future of TV? The case considers Samsung Electronics TV Group's product development processes, as the company's mobile and TV offerings increasingly converged and consumer demands and behavior pushed the historically clear boundaries of product, content, engagement and interaction.

In late 2013, Rajeev Kulkarni needed to decide how best to facilitate the emergence of a broad base of users and content to promote the sale of 3D Systems' consumer-focused 3D printers. As yet, neither the company nor users had identified an indispensable application for 3D printing for consumers, despite a plethora of potential opportunities.

In May 2014, Bill McDermott will become the sole CEO of SAP AG, the world leader in the Enterprise Resource Planning (ERP) field. The case occurs in January 2014 at SAP's investors meeting, at a time when the company's stock is near record high. A 2010 strategy committed the company to a transition to cloud computing. The main driver behind this transition was the development of SAP HANA, an in-memory computing technology that combined database, data processing, and application platform functionality. Ownership of cloud infrastructure was a key question. SAP could build, own, and operate its own data centers, or partner to locate SAP HANA and other products with other cloud infrastructure providers, such as Amazon, Microsoft, or IBM. McDermott also had to make decisions around the organization and leadership of the company's cloud efforts.

This supplementary case follows up on an innovative R&D approach by Beiersdorf,a skin care and cosmetics company. The case relates what happened to the product launched by Beiersdorf, to its Nivea line, following the events of the A case, and how the commercial success of the product informed thinking by leaders in R&D for the future.

The case describes the efforts of Beiersdorf, a worldwide leader in the cosmetics and skin care industries, to generate and commercialize new R&D through open innovation using external crowds and "netnographic" analysis. Beiersdorf, best known for its consumer brand Nivea, has a rigorous R&D process that has led to many successful product launches, but are there areas of customer need that are undervalued by the traditional process? A novel online customer analysis approach suggests untapped opportunities for innovation, but can the company justify a launch based on this new model of research?

This note provides information on the state of startup financing in Silicon Valley in 2013. It details different avenues startups have to raise funding, including venture capital, corporate venture capital, angel investors, incubators, and crowdfunding.

By 2013, Google, while not a traditional manufacturer of automobiles, had invested millions of dollars in its self-driving cars which had logged over 500,000 miles of testing. The Google management team faced several questions. Should Google continue to invest in the technology behind self-driving cars? How could Google's core software-based and search business benefit from self-driving car technology? As large auto manufacturers began to invest in automotive technology themselves, could Google compete? Was this investment of time and resources worth it for Google?

The case describes Siemens, a worldwide innovator in the Energy, Healthcare, Industry, and Infrastructure & Cities sectors, and its efforts to develop and commercialize new R&D through open innovation, including internal and external crowdsourcing contests. Emphasis is placed on exploring actual open innovation initiatives within Siemens and their outcomes. These include creating internal social- and knowledge-sharing networks and utilzing third party platforms to host internal and external contests. Industries discussed include energy, green technology, infrastructure and cities, and sustainability. In addition, the importance of fostering a collaborative online environment and protecting intellectual property is explored.

The case describes OpenIDEO, an online offshoot of IDEO, one of the world's leading product design firms. OpenIDEO leverages IDEO's innovative design process and an online community to create solutions for social issues. Emphasis is placed on comparing the IDEO and OpenIDEO processes using real-world project examples. For IDEO this includes the redesign of Air New Zealand's long haul flights. For OpenIDEO this includes increasing bone marrow donor registrations and improving personal sanitation in Ghana. In addition, the importance of fostering a collaborative online environment is explored.

Metrology plays a key role in the manufacture of mechanical components. Traditionally it is used extensively in a pre-process stage where a manufacturer does process planning, design, and ramp-up, and in post-process off-line inspection to establish proof of quality. The area that is seeing a lot of growth is the in-process stage of volume manufacturing, where feedback control can help ensure that parts are made to specification. The Industrial Metrology Group at Carl Zeiss AG had its traditional strength in high precision coordinate measuring machines, a universal measuring tool that had been widely used since its introduction in the mid-1970s. The market faced a complex diversification of competition as metrology manufacturers introduced new sensor and measurement technologies, and as some of their customers moved towards a different style of measurement mandating speed and integration with production systems. The case discusses the threat of new in-line metrology systems to the core business as well as the arising new opportunities.

InnoCentive.com enables clients to tap into internal and external solver networks to address various business issues. In 2008, InnoCentive introduced "InnoCentive@Work" (lC@W), which recognized clients' reluctance to share problems and solutions with an external network. Instead, IC@W enabled clients to foster open collaboration amongst its own employees. IC@W became the fastest growing product in InnoCentive's portfolio. In 2010, InnoCentive added "team project rooms" which allowed small groups of solvers from InnoCentive's community to openly add posts and discussion threads after agreeing to the confidentiality and IP transfer requirements of the client. The case raises the questions of how the team room concept could be improved and how clients could be convinced of its benefits.

InnoCentive.com enables clients to tap into internal and external solver networks to address various business issues. This case focuses on the outcome of InnoCentive's decision to post challenges related to environmental issues created by the Gulf Oil Spill. It reviews lessons learned from this experience and asks students to consider whether InnoCentive should post challenges in response to the nuclear crises resulting from the 2011 Japanese earthquake and tsunami.

This case presents the logic and execution underlying the launch of Data.gov, an instantiation of President Obama's initiative for transparency and open government. The process used by Vivek Kundra, the federal CIO, and his team to rapidly develop the website and to make available high-value data sets for reuse is highlighted. The case recounts Kundra's experience at the state and local government levels in developing open data initiatives and the application of that experience to the federal government. The case demonstrates the benefits of making government data available in terms of both engaged citizens and the potential for new innovations from the private sector. Potential drawbacks of open access including security and privacy issues are illustrated. Issues related to the role of government in releasing data and the balance between accountability and private-sector innovation are explored.

This case presents the Myelin Repair Foundation's accelerated research collaboration model for drug discovery. It highlights the challenges of building a multi-disciplinary and multi-institutional research collaboration that is attempting to create a treatment for multiple sclerosis based on a novel scientific approach. The case provides details on how norms of academic research and intellectual property had to be updated to enable collaboration. The current dilemma facing the CEO and COO of the foundation relates to setting strategic priorities for research so that a treatment for MS can be ready in the next ten years. The strategic choices need to account for the complexities of drug discovery, the uncertainty of commercial partners' interest in the therapeutic approach and the constrained donor-based fundraising environment.

TopCoder's crowdsourcing-based business model, in which software is developed through online tournaments, is presented. The case highlights how TopCoder has created a unique two-sided innovation platform consisting of a global community of over 225,000 developers who compete to write software modules for its over 40 clients. Provides details of a unique innovation platform where complex software is developed through ongoing online competitions. By outlining the company's evolution, the challenges of building a community and refining a web-based competition platform are illustrated. Experiences and perspectives from TopCoder community members and clients help show what it means to work from within or in cooperation with an online community. In the case, the use of distributed innovation and its potential merits as a corporate problem solving mechanism is discussed. Issues related to TopCoder's scalability, profitability, and growth are also explored.

InnoCentive.com, a firm connecting R&D labs of large organizations to diverse external solvers through innovation contests, has to decide if it will enable collaboration in its community. Case covers the basics of a distributed innovation system works and the advantages of having external R&D. Links how concepts of open source are applied to a non-software setting. Describes the rationale for participation by solvers in innovation contests and the benefits that accrue to firms. Raises the issue if a community can be shifted to collaboration when competition was the basis of prior interaction.

Business ecosystems require careful orchestration and strategic choices regarding make/buy/partner decisions and membership access. This case examines the strategic and technological issues related to managing SAP's thriving ecosystem of user communities, software vendors, integration partners, and technology providers. It details how the ecosystem gets developed and the challenges in meeting the needs of the internal organization, large partners, and small up-and-coming firms. SAP executives, in this case, have to make a decision if a relatively small startup firm should be elevated to the highest strategic partnership level, normally reserved for very large firms.

Threadless.com, the online, Chicago-based t-shirt company, was not your typical fashion apparel company. The company, run by Jake Nickell, Jacob DeHart, and Jeffrey Kalmikoff, turned the fashion business on its head by enabling anyone to submit designs for t-shirts and asking its community of more than 500,000 members to help select winning designs. Threadless encouraged community members to actively participate by critiquing submitted designs, blogging about their daily lives, posting songs and videos inspired by the designs, and, most important, purchasing t-shirts that have won the weekly design competitions. In 2007, Threadless was well on its way to selling more than a million and a half t-shirts. The success of Threadless has garnered significant media attention, the New York Times and USA's National Public Radio highlighting its unique community-based business model and has piqued the interest of large traditional retailers. Nickell, DeHart, and Kalmikoff were now faced with making a decision about a potentially lucrative offer from a major retailer offering to carry large volumes of select Threadless t-shirts in its retail stores. Should they accept?

The instructor version of Threadless includes the Threadless student version multimedia case as well as four additional videos that can be used to enhance class discussion. The first video presents community reaction to the proposal from the large retailer. The next two videos detail the rationale for the final decision and their future plans. The final video contains a discussion about community participation and questions of exploitation.

Cambrian House builds internet-based products and services by relying entirely on its user community for all aspects of its innovation and new product development process. Users suggest ideas for new products and services and also participate in a monthly voting process to select the best ideas. The company is now considering the deployment of a prediction market to deepen user involvement and commitment in its innovation; however, it is not sure if it is an appropriate strategy for its community.

In its eight quarters of operation, Google's internally developed prediction market has delivered accurate and decisive predictions about future events of interest to the company. Google must now determine how to increase participation in the market, and how to best use its predictions.

Wikipedia has emerged as a robust model for content production by volunteers working asynchronously on the Internet with a unconventional model for distributed decision making. The "Articles for Deletion" process in Wikipedia provides unique insight into the inner workings of a distributed community. Wikipedia administrators have to decide if an article on "Enterprise 2.0" should be deleted, kept or merged with some other article. The episode illustrates broader issues of IT-enabled community mobilization and engagement in distributed setting.

Awards & Honors

Winner of the 2015 Case Centre Award in the Production and Operations Management category for “Open Innovation at Siemens” with Katja Hutter, Stephanie Healy Pokrywa, and Johann Fuller (HBS Case 613-100).

Finalist for the 2013 McKinsey Award for the best article in Harvard Business Review for “Using the Crowd as an Innovation Partner” with Kevin J. Boudreau (April 2013).

Finalist for the 2013 Best Paper in Management Science from the Manufacturing and Service Operations Management Society for “Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis” with Kevin J. Boudreau and Nicola Lacetera (May 2011).

Received the 2011 Innovative Management Partner (IMP) Excellence in Innovation Research Award from Innsbruck University School of Management.

Winner of the 2008 TUM Research Excellence Award in Innovation and Leadership from Technische Universität München and the Peter Pribilla Foundation.

Finalist for the 2006 Best Dissertation Award from the Technology and Innovation Management Division of the Academy of Management.

Recipient of the 2006 Brad W. Hosler Outstanding Student Paper Award at the Portland International Conference on Management of Engineering and Technology.